Senior Machine Learning Engineer - LLM/RAG

Key Responsibilities :

- Provide technical leadership in ASR (Automatic Speech Recognition), TTS (Text-to-Speech), Dialogue Systems, LLMs, and RAG (Retrieval-Augmented Generation).

- Architect and implement scalable, low-latency ML systems for real-time Voice AI applications.

- Mentor, coach, and guide junior ML engineers to build internal capability.

- Drive the end-to-end lifecycle of ML projects including ideation, prototyping, deployment, and iteration.

- Collaborate closely with leadership across product, engineering, and research to align technical efforts with business strategy.

- Contribute to innovation by exploring emerging techniques like State Space Models (Mamba, Hamba).

- Ensure best practices in cloud-based deployment (AWS, GCP, Azure) for scalable solutions.

Requirements :

- Bachelors degree in Computer Science/Engineering or related field; MS/PhD preferred.

- Strong academic foundation, ideally from Tier-1 institutions (IIT, IIIT, IISc, BITS, top NITs).

- Deep expertise in Voice AI, Speech ML, and LLMs.

- Hands-on proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX.

- Proven track record of delivering ML systems into production at scale.

- Prior experience in leading and mentoring ML engineering teams.

- Experience building multilingual AI solutions for diverse user bases.

- Strong background in model optimization, real-time performance tuning, and data pipeline design.

- Familiarity with modern State Space Models (Mamba, Hamba, etc.) is highly desirable.

- Excellent problem-solving, collaboration, and communication skills.